Necessary and Sufficient

To understand the current sovereign debt problems in Europe one has to understand the monetary policy options available to the government of a sovereign state. Basically, there are several options available to manage national debt:

1. Print More Money
2. Devalue the Currency
3. Raise Taxes
4. Raise More Money
5. Default

Let's run through each of these options and consider how it applies to the current Greek situation, and perhaps soon to Spain and Portugal.

Print More Money

The majority of Greece's public debt is denominated in Euros - the "local" currency - which means that it could simply print more money to pay off its large debts (you can't do this if your debt is denominated in foreign currencies). Printing more of the local currency does have consequences - it causes inflation which effectively reduces the nominal value of all other debt denominated in the local currency.

However there is a problem here. Although technically and legally a sovereign state, the Greek government doesn't have all the fiscal options usually available to an independent nation. Because it uses the Euro, and that is a shared currency with other nations, it cannot simply print more money because that's controlled by the monetary union of the euro zone. This restriction is in place to prevent other member nations from suffering currency devaluations should a member nation decide to print more of the shared currency (Euros).

Problem one.

Devalue the Currency
A government can devalue its local currency to make the domestic currency cheaper relative to other currencies. There are two implications of a devaluation. First, devaluation makes the country's exports relatively less expensive for foreigners. Second, the devaluation makes foreign products relatively more expensive for domestic consumers, thus discouraging imports. This may help to increase the country's exports and decrease imports, and may therefore help to reduce the current account deficit.

However, for the same reasons stated above - the usage of a shared currency - Greece is unable to devalue its "local" currency because its not in control of the Euro.

Problem two!!

Cut Public Spending and Raise Taxes
To increase its revenue intake the Government can raise taxes in an effort to help pay down the public debt. This is politically unpopular and thus most governments are reluctant to consider it, unless backed into a corner. Greece is doing this, but due to the magnitude of public debt it's going to find it quite difficult to raise enough money fast enough using just this option. It's been reported that Greece owes 300 billion euros which represents a public deficit of 14% of the GDP.

Problem three!!! Now into the "options of last resort"...

Raise More Money
Despite having debt problems, in order to service debts falling due Greece needs to raise more money through issuance of Government Bonds however this is a short-term solution at best. Its been reported that Greece needs to raise some 30+ billion Euros just to meets its obligations for the next 12 months. Taking on new debt obviously doesn't solve the problem of indebtedness long term, and flooding the market with sovereign bonds at a time when many investors think a default is likely causes investors to demand higher yields which makes debt raising a very expensive option.

Problem four!!!!

Default on its Debt
Defaulting on its debt would cause Greece's sovereign credit rating to decrease causing it have to pay more for future borrowings, and industry also suffers. But because Greece is a member nation of the Euro zone any default on its behalf also affects other euro-nations like Germany, Spain, Portugal, and Italy.

A default is likely unless a sufficient large bailout package from the IMF and/or other Euro-nations gets put in place along with other measures. The 3-year 110 million euro package currently on offer courtesy of the IMF is a good start!

Conclusion
Moral of the story... if you let your debt get out of control you are in for a lengthy period of financial hardship to recover. Indeed, that is what Greece currently faces, and its citizens will have little respect for the politicians responsible for monetary policy for letting such an unpleasant situation happen in the first place.

WSJ journalist Scott Patterson has jumped on the bandwagon suggesting that quants where a major cause of the GFC...

Conventional wisdom says that quants formulate models in conjunction with traders. Once developed they tell the traders how the model internals works, pointing out assumptions and limitations so that an informed opinion can be formed about when the model should be applied and when it's not going to work. Quants should be able to quantify the risk and expected loss under certain "bad" scenarios.

When the trading model is in operation, further up the chain back-office track exposures and risk, and at the very top bank executives have overall control of the allocation of capital to trading desks. Thus there are many levels of accountability: the quant, the traders, back-office, and executives. If people other than the quants don't understand the models and their application then they ought to be very caution about applying then.

I don't see that as a failure of quants. Sure, not all models are well thought out but in my mind it's a failure of risk management, or a strong preference by bank executives for profit over prudent risk management that is more to blame than the quants.

Investment banks and hedge funds have a healthy appetite for hiring brainy "quants" - usually in the form of well-qualified mathematicians and physicists - to help them understand and model the markets using complex mathematics. It's called quantitiative finance, and it's being blamed in-part for the current GFC. How so? Well the root of most of the evil for the smouldering balance sheets of many banks are the infamous collateralized debt obligations (CDOs) - those funky instruments crafted by slicing and dicing large numbers of ordinary loans before selling them off to investors. They are the most common form of structured credit and have now been labelled by many as "toxic assets".

CDOs have been around since the late 80s but they only came to prominence in 2000 when new mathematical models were invented that, apparently, made it significantly easier to price CDOs. The quant responsible for the new model was David X. Li, a mathematician working at JPMorgan. His model was called the Gaussian Copula Function which, in essence, is a formula to determine the correlation between the default rates of different securities.

In other words, if the model was correct, it would tell you the likelihood that related CDOs will explode - important information in the pricing of CDOs and in risk management of CDO portfolios. Since these CDOs were in the hands of many larger corporations the model was also a predictor of the likelihood that a given set of corporations would default on their bond debt in quick succession. Naturally this measure of counter-party risk is something you want to know before buying such instruments from another bank. Because of the new simpler model the CDO market swelled in volume and every large bank in the world had exposure to these instruments. Many believed David Li was on his way to a Nobel prize, and worldwide acknowledgement for his contribution.

As profit margins on CDOs reduced and bankers were looking for more loans for securitisation they ventured into sub-prime housing loans and packaged lesser quality loans into CDOs. Then the market starting doing things the model hadn't expected. Time has shown that the true risk associated with default rates on these loans and the effect on the prices of the related CDOs was not at all explained by the Guassian Copula function. Since the majority of financial institutions had exposure to these CDOs there was heavy reliance on the Guassian Copula function in the pricing and risk management of these instruments. Couple that with a model built on assumptions that weren't extensively tested by people putting the model to use, and a significant rise in sub-prime home loan defaults due to dubious lending decisions and you get the financial meltdown that is the GFC.

Many experts believe one of the fundamental drivers of the GFC was the significant rise of sub-prime loan defaults. Actuaries and mathematicians are adept are deriving probabilities for stochastic events like a loan default but they generally seek greater accuracy by grouping a large number of data points together into a risk pool. When this pooling is done it's preferred that the data points being pooled are independent random events but this is not always possible. To see this, consider a simple example of home loan defaults: If Bob were to default on his 250k loan, you would think that it would have no effect on the default likelihood of another customer, Charlie, who also has a 250k loan and earns roughly the same amount of money as Bob. That is, the two random events/variables are uncorrelated. But what if Bob and Charlie both work at the same company and the reason Bob defaulted was because his employer shut down and he was suddenly out of a job? It would mean that Charlie would also be out of job and he may not be able to secure a new job and default just like Bob did. In other words, there is a correlation between the two random events because of the same-employer linkage. And there could be other correlations between groups of people in the risk pool based on other factors - like tolerance to interest rate rises, or home devaluations in a particular geographic region due to market conditions or acts of god. Statisticians have ways to deal with such multicollinearity (correlations between seemingly independent random variable) but in reality, the common linkage between borrowers in a loan pool are extremely complex and difficult to analyse.

Mathematicians realised that they needed to account for these correlations but determining conditional probability distributions to model correlations requires lots of historical data and a large degree of computational analysis. Li's formula simplified this greatly thus making the analysis considerably more tractable. Perhaps not fully understanding it, many quants and trading desks adopted the model and assumed it to be accurate.

The quants are the people Warren Buffett was talking about when he said, "Beware of geeks bearing formulas" in his letter to shareholders this year. However, the quants aren't entirely to blame for the financial meltdown; there's plenty of guilt to be shared by regulators, top executives and the investors who bought the instruments the quants created!

To be fair, Li warned that the "most dangerous part is when people believe everything coming out of the model".